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Content Distribution Networks (CDNs)

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Content Distribution Networks (CDNs) Mike Freedman ... (DHTs), and overlay networks Network case studies Enterprise, wireless, cellular, datacenter, ... – PowerPoint PPT presentation

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Title: Content Distribution Networks (CDNs)


1
Content Distribution Networks (CDNs)
  • Mike Freedman
  • COS 461 Computer Networks
  • Lectures MW 10-1050am in Architecture N101
  • http//www.cs.princeton.edu/courses/archive/spr13/
    cos461/

2
Second Half of the Course
  • Application case studies
  • Content distribution, peer-to-peer systems and
    distributed hash tables (DHTs), and overlay
    networks
  • Network case studies
  • Enterprise, wireless, cellular, datacenter, and
    backbone networks software-defined networking
  • Network security
  • Securing communication protocols
  • Interdomain routing security

3
Single Server, Poor Performance
  • Single server
  • Single point of failure
  • Easily overloaded
  • Far from most clients
  • Popular content
  • Popular site
  • Flash crowd (aka Slashdot effect)
  • Denial of Service attack

4
Skewed Popularity of Web Traffic
  • Zipf or power-law distribution

Characteristics of WWW Client-based Traces Carlos
R. Cunha, Azer Bestavros, Mark E. Crovella,
BU-CS-95-01
5
Web Caching
6
Proxy Caches
6
origin server
Proxy server
HTTP request
HTTP request
client
HTTP response
HTTP response
HTTP request
HTTP response
client
7
Forward Proxy
  • Cache close to the client
  • Under administrative control
  • of client-side AS
  • Explicit proxy
  • Requires configuring browser
  • Implicit proxy
  • Service provider deploys an on path proxy
  • that intercepts and handles Web requests

Proxy server
HTTP request
client
HTTP response
HTTP request
HTTP response
client
8
Reverse Proxy
  • Cache close to server
  • Either by proxy run by server or in third-party
    content distribution network (CDN)
  • Directing clients to the proxy
  • Map the site name to the IP address of the proxy

origin server
Proxy server
HTTP request
HTTP response
HTTP request
HTTP response
origin server
9
Google Design
Private Backbone
Internet
Client
Client
10
Proxy Caches
  • (A) Forward (B) Reverse (C) Both (D)
    Neither
  • Reactively replicates popular content
  • Reduces origin server costs
  • Reduces client ISP costs
  • Intelligent load balancing between origin servers
  • Offload form submissions (POSTs) and user auth
  • Content reassembly or transcoding on behalf of
    origin
  • Smaller round-trip times to clients
  • Maintain persistent connections to avoid TCP
    setup delay (handshake, slow start)

11
Proxy Caches
  • (A) Forward (B) Reverse (C) Both (D)
    Neither
  • Reactively replicates popular content (C)
  • Reduces origin server costs (C)
  • Reduces client ISP costs (A)
  • Intelligent load balancing between origin servers
    (B)
  • Offload form submissions (POSTs) and user auth
    (D)
  • Content reassembly, transcoding on behalf of
    origin (C)
  • Smaller round-trip times to clients (C)
  • Maintain persistent connections to avoid TCP
    setup delay (handshake, slow start) (C)

12
Limitations of Web Caching
  • Much content is not cacheable
  • Dynamic data stock prices, scores, web cams
  • CGI scripts results depend on parameters
  • Cookies results may depend on passed data
  • SSL encrypted data is not cacheable
  • Analytics owner wants to measure hits
  • Stale data
  • Or, overhead of refreshing the cached data

13
Modern HTTP Video-on-Demand
  • Download content manifest from origin server
  • List of video segments belonging to video
  • Each segment 1-2 seconds in length
  • Client can know time offset associated with each
  • Standard naming for different video resolutions
    and formats e.g., 320dpi, 720dpi, 1040dpi,
  • Client downloads video segment (at certain
    resolution) using standard HTTP request.
  • HTTP request can be satisfied by cache its a
    static object
  • Client observes download time vs. segment
    duration, increases/decreases resolution if
    appropriate

14
Content Distribution Networks
15
Content Distribution Network
origin server in North America
  • Proactive content replication
  • Content provider (e.g., CNN) contracts with a CDN
  • CDN replicates the content
  • On many servers spread throughout the Internet
  • Updating the replicas
  • Updates pushed to replicas when the content
    changes

CDN distribution node
CDN server in S. America
CDN server in Asia
CDN server in Europe
16
Server Selection Policy
  • Live server
  • For availability
  • Lowest load
  • To balance load across the servers
  • Closest
  • Nearest geographically, or in round-trip time
  • Best performance
  • Throughput, latency,
  • Cheapest bandwidth, electricity,

Requires continuous monitoring of liveness, load,
and performance
17
Server Selection Mechanism
  • Application
  • HTTP redirection
  • Advantages
  • Fine-grain control
  • Selection based on client IP address
  • Disadvantages
  • Extra round-trips for TCP connection to server
  • Overhead on the server

GET
Redirect
GET
OK
18
Server Selection Mechanism
  • Advantages
  • No extra round trips
  • Route to nearby server
  • Disadvantages
  • Does not consider network or server load
  • Different packets may go to different servers
  • Used only for simple request-response apps
  • Routing
  • Anycast routing

19
Server Selection Mechanism
  • Advantages
  • Avoid TCP set-up delay
  • DNS caching reduces overhead
  • Relatively fine control
  • Disadvantage
  • Based on IP address of local DNS server
  • Hidden load effect
  • DNS TTL limits adaptation
  • Naming
  • DNS-based server selection

1.2.3.4
DNS query
1.2.3.5
local DNS server
20
How Akamai Works
21
Akamai Statistics
  • Distributed servers
  • Servers 100,000
  • Networks 1,000
  • Countries 70
  • Many customers
  • Apple, BBC, FOX, GM IBM, MTV, NASA, NBC, NFL,
    NPR, Puma, Red Bull, Rutgers, SAP,
  • Client requests
  • Hundreds of billions per day
  • Half in the top 45 networks
  • 15-20 of all Web traffic worldwide

22
How Akamai Uses DNS
22
HTTP
cnn.com (content provider)
DNS root server
GET index.html
Akamai cluster
Akamai global DNS server
http//cache.cnn.com/foo.jpg
1
2
HTTP
Akamai regional DNS server
Nearby Akamai cluster
End user
23
How Akamai Uses DNS
23
HTTP
cnn.com (content provider)
DNS TLD server
DNS lookup cache.cnn.com
Akamai cluster
Akamai global DNS server
3
1
2
ALIAS g.akamai.net
4
Akamai regional DNS server
Nearby Akamai cluster
End user
24
How Akamai Uses DNS
24
HTTP
cnn.com (content provider)
DNS TLD server
DNS lookup g.akamai.net
Akamai cluster
Akamai global DNS server
5
3
1
2
6
4
Akamai regional DNS server
ALIAS a73.g.akamai.net
Nearby Akamai cluster
End user
25
How Akamai Uses DNS
25
HTTP
cnn.com (content provider)
DNS TLD server
Akamai cluster
Akamai global DNS server
5
3
1
2
6
4
Akamai regional DNS server
7
DNS a73.g.akamai.net
8
Address 1.2.3.4
Nearby Akamai cluster
End user
26
How Akamai Uses DNS
26
HTTP
cnn.com (content provider)
DNS TLD server
Akamai cluster
Akamai global DNS server
5
3
1
2
6
4
Akamai regional DNS server
7
8
9
Nearby Akamai cluster
End user
GET /foo.jpg Host cache.cnn.com
27
How Akamai Uses DNS
27
HTTP
cnn.com (content provider)
DNS TLD server
GET foo.jpg
11
12
Akamai cluster
Akamai global DNS server
5
3
1
2
6
4
Akamai regional DNS server
7
8
9
Nearby Akamai cluster
End user
GET /foo.jpg Host cache.cnn.com
28
How Akamai Uses DNS
28
HTTP
cnn.com (content provider)
DNS TLD server
11
12
Akamai cluster
Akamai global DNS server
5
3
1
2
6
4
Akamai regional DNS server
7
8
9
Nearby Akamai cluster
End user
10
29
How Akamai Works Cache Hit
29
HTTP
cnn.com (content provider)
DNS TLD server
Akamai cluster
Akamai global DNS server
1
2
Akamai regional DNS server
3
4
5
Nearby Akamai cluster
End user
6
30
Mapping System
  • Equivalence classes of IP addresses
  • IP addresses experiencing similar performance
  • Quantify how well they connect to each other
  • Collect and combine measurements
  • Ping, traceroute, BGP routes, server logs
  • E.g., over 100 TB of logs per days
  • Network latency, loss, and connectivity

31
Mapping System
  • Map each IP class to a preferred server cluster
  • Based on performance, cluster health, etc.
  • Updated roughly every minute
  • Map client request to a server in the cluster
  • Load balancer selects a specific server
  • E.g., to maximize the cache hit rate

32
Adapting to Failures
  • Failing hard drive on a server
  • Suspends after finishing in progress requests
  • Failed server
  • Another server takes over for the IP address
  • Low-level map updated quickly
  • Failed cluster
  • High-level map updated quickly
  • Failed path to customers origin server
  • Route packets through an intermediate node

33
Akamai Transport Optimizations
  • Bad Internet routes
  • Overlay routing through an intermediate server
  • Packet loss
  • Sending redundant data over multiple paths
  • TCP connection set-up/teardown
  • Pools of persistent connections
  • TCP congestion window and round-trip time
  • Estimates based on network latency measurements

34
Akamai Application Optimizations
  • Slow download of embedded objects
  • Prefetch when HTML page is requested
  • Large objects
  • Content compression
  • Slow applications
  • Moving applications to edge servers
  • E.g., content aggregation and transformation
  • E.g., static databases (e.g., product catalogs)

35
Conclusion
  • Content distribution is hard
  • Many, diverse, changing objects
  • Clients distributed all over the world
  • Reducing latency is king
  • Contribution distribution solutions
  • Reactive caching
  • Proactive content distribution networks
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